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If you check Create links to source data, Excel creates a link to your source data (your consolidated data will be updated if your source data changes) and creates an outline. Because our worksheets are not identical, we want Excel to sum cells that have the same labels. For example, cell B2 (in district1.xlsx) + cell B2 (in district2.xlsx) + cell B2 (in district3.xlsx). Note: if you don't check Top row and Left column, Excel sums all cells that have the same position. Check Top row, Left column and Create links to source data. Repeat step 4 for the district2 and district3 workbook.Ħ. Click in the Reference box, select the range A1:E4 in the district1 workbook, and click Add.ĥ. Choose the Sum function to sum the data.Ĥ. On the Data tab, in the Data Tools group, click Consolidate.ģ. This is a lot easier than creating formulas.Ģ. However, the beauty of the Consolidate feature is that it can easily sum, count, average, etc this data by looking at the labels. X = X.reshape((X.shape, X.shape, X.As you can see, the worksheets are not identical. Last_sequence = np.array(pd.DataFrame(last_sequence).shift(-1).dropna()) Last_sequence = list(sequences) + list(last_sequence) To perform this step, find the Insert tab and. To do this, click and drag the mouse over the cells with the data sets to select. Combining Data Sets into a Graph The first step in combining two graphs is selecting the data sets that will go into the graph. # this last_sequence will be used to predict in future dates that are not available in the dataset This process takes several steps to complete. # for instance, if n_steps=50 and lookup_step=10, last_sequence should be of 59 (that is 50+10-1) length # get the last sequence by appending the last `n_step` sequence with `lookup_step` sequence

Last_sequence = np.array(df.tail(lookup_step))įor entry, target in zip(df.values, df.values): # last `lookup_step` columns contains NaN in future column

# add the target column (label) by shifting by `lookup_step`ĭf = df.shift(-lookup_step) # add the MinMaxScaler instances to the result returned I understand a new version with Yahoo finance is in the worksany idea when it could be released or any other excel based stock evaluator similar to yours that.

Raise RemoteDataError('Unable to read URL: ' does not exist in the dataframe."ĭf = scaler.fit_transform(np.expand_dims(df.values, axis=1)) Response = self._get_response(url, params=params)įile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/base.py", line 120, in _get_response Out = self._read_url_as_StringIO(url, params=params)įile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/base.py", line 85, in _read_url_as_StringIO RemoteDataError: No data fetched using 'YahooDailyReader'įile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/data.py", line 117, in DataReaderįile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/yahoo/daily.py", line 77, in readĭf = super(YahooDailyReader, self).read()įile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/base.py", line 157, in readįile "./venv3.5/lib/python3.5/site-packages/pandas_datareader/base.py", line 74, in _read_one_data name))ġ99 if len(stocks) > 0 and len(failed) > 0 and len(passed) > 0: > 197 raise RemoteDataError(msg.format(self. > 178 df = self._dl_mult_symbols(self.symbols)Ĭ:\Users\randomname\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas_datareader\base.py in _dl_mult_symbols(self, symbols) > 77 df = super(YahooDailyReader, self).read()ħ9 df = _calc_return_index(df)Ĭ:\Users\randomname\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas_datareader\base.py in read(self)ġ76 df = self._dl_mult_symbols() > 6 INPX = data.DataReader(INPX ,'yahoo', start, end)Ĭ:\Users\randomname\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas_datareader\data.py in DataReader(name, data_source, start, end, retry_count, pause, session)Ĭ:\Users\randomname\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas_datareader\yahoo\daily.py in read(self)ħ6 """ read one data from specified URL """ RemoteDataError Traceback (most recent call last) Please correct me if this is not the correct place to put this.